Back

Timing and Predictors of Loss of Infectivity among Healthcare Workers with Primary and Recurrent COVID-19: a Prospective Observational Cohort Study

Dzieciolowska, S.; Charest, H.; Roy, T.; Fafard, J.; Carazo, S.; Levade, I.; Longtin, J.; Parkes, L.; Beaulac, S. N.; Villeneuve, J.; Savard, P.; Corbeil, J.; De Serres, G.; Longtin, Y.

2023-06-18 infectious diseases
10.1101/2023.06.16.23291449 medRxiv
Show abstract

BackgroundThere is a need to understand the duration of infectivity of primary and recurrent COVID-19 and identify predictors of loss of infectivity. MethodsProspective observational cohort study with serial viral culture, rapid antigen detection test (RADT) and RT-PCR on nasopharyngeal specimens of healthcare workers with COVID-19. The primary outcome was viral culture positivity as indicative of infectivity. Predictors of loss of infectivity were determined using multivariate regression model. The performance of the US CDC criteria (fever resolution, symptom improvement and negative RADT) to predict loss of infectivity was also investigated. Results121 participants (91 female [79.3%]; average age, 40 years) were enrolled. Most (n=107, 88.4%) had received [&ge;]3 SARS-CoV-2 vaccine doses, and 20 (16.5%) had COVID-19 previously. Viral culture positivity decreased from 71.9% (87/121) on day 5 of infection to 18.2% (22/121) on day 10. Participants with recurrent COVID-19 had a lower likelihood of infectivity than those with primary COVID-19 at each follow-up (day 5 OR, 0.14; p<0.001]; day 7 OR, 0.04; p=0.003]) and were all non-infective by day 10 (p=0.02). Independent predictors of infectivity included prior COVID-19 (adjusted OR [aOR] on day 5, 0.005; p=0.003), a RT-PCR Ct value <23 (aOR on day 5, 22.75; p<0.001), but not symptom improvement or RADT result. The CDC criteria would identify 36% (24/67) of all non-infectious individuals on Day 7. However, 17% (5/29) of those meeting all the criteria had a positive viral culture. ConclusionsInfectivity of recurrent COVID-19 is shorter than primary infections. Loss of infectivity algorithms could be optimized.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.